FAQ: Generating Text with Deep Learning - Build and Train seq2seq

This community-built FAQ covers the “Build and Train seq2seq” exercise from the lesson “Generating Text with Deep Learning”.

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This exercise can be found in the following Codecademy content:

Natural Language Processing

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Hi,

I’m struggling to understand the connection between encoder and decoder. A couple of questions:

  1. How do they fit in the entire LSTM framework? Does one neuron in the network have both?
  2. What are hidden and cell states and how do they differ from each other? Is there any distinction on what they represent and/or their purpose is?
  3. About the activation functions in each neuron visualized in the reading section (the part before this lesson), where do those fit in our seq2seq model?

Any help would be appreciated. Cheers :slight_smile: